DEBATE Are Schools of Public Health Needed to Address Public Health Workforce Development in
Bibliographic record
Abstract
In addition to establishing Canadian federal institutions for public health to work in cooperation with provincial and local health authorities, the infrastructure of public health for the future depends on a multi-disciplinary and well-prepared workforce. Traditionally, Canada trained its public health workforce in schools of public health (or hygiene), but in recent decades this has been carried out in departments and centres primarily within medical faculties. Recent public health crises in Canada have led to some new federal institutions and reorganization of public health activities as well as other reforms. This commentary proposes re-examination of the context of public health workforce training and especially for schools of public health as independent faculties within universities as in the United States or, as developed more recently in Europe, semi-independent schools within medical faculties. The multi-disciplinary nature of public health professionals and the complex challenges of the “New Public Health ” call for a new debate on this vital issue of public health workforce development. Public health needs a new image and higher profile of training, research and service to meet provincial and national needs,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.018 | 0.034 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.051 | 0.047 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".